FI129350B - Information system for a district heating network and method in connection with the district heating network - Google Patents

Abstract

The invention relates to an information system for a district heating network (100) comprising • at least one power plant (102), • a heat distribution network including branched heat transfer pipelines (104) and pumping stations (106), and • numerous customer properties (110) with their own heat ) comprising heat exchangers (50) and a control system (20) for controlling the district heating flow according to the set consumption and own metering equipment including means for collecting metering data from a customer system adapted to collect information from customer properties (110) to meet the requirements of the client properties (110) in accordance with a pre-selected criterion. In addition, • in at least several customer properties (110), the metering equipment includes a control unit (70) for calculating a key-performance-index (KPI) value from the relative capacity data according to a preselected calculation criterion, recording the KPI and transmitting the KPI to the heat sink. adapted to provide real-time information on the heat supply status of the customer properties (110) to the heat producer in reduced information bundles comprising at least a KPI value of said customer property (110) and identification data of the customer property (110), and • display means for displaying said KPI value to the heat producer. The invention also relates to a corresponding method in connection with a district heating network (100).

Description

INFORMATION SYSTEM - FOR DISTRICT HEATING NETWORK AND METHOD

The invention relates to an information system for a district heating network comprising e at least one power plant, e a heat distribution network including branched heat transfer pipelines and pumping stations, and a number of customer properties with according to consumption and its own measuring equipment, which includes means for collecting measurement data from the customer system. The information system is adapted to collect information from customer properties on the status of heat supply, enabling the heat producer to adjust the heat production parameters of the district heating network on the basis of user-specific information to meet the requirements of the customer properties according to a pre-selected criterion. The invention also relates to a corresponding method. In the current district heating network ('/ Suomalainen district heating' ', Veli-Matti Mäkelä and Jarmo Tuunanen), the Q measuring center for customer equipment includes a heat meter with N 25 connected flow and return temperature sensors and a flow sensor. The readings of the metering devices are transferred from the customer property to the heat seller using remote reading 2. Real-time information from the measuring devices can also be provided to the customer 2 for consumption control. By measuring, billing volumes, energy consumption data, production volumes, heat losses, information related to energy savings and information required by various services are determined. The heat distribution center for customer properties

The gauges also allow alarms for temperatures, pressure levels and other functions.

The pipelines in the district heating network include measuring devices that handle flow and energy measurements, temperature measurements, and pressure and differential pressure measurements, which can be used to monitor the state of heat supply.

However, in current district heating networks, the power plant often does not have any real-time information on the fulfillment of the criteria set for the heat supply of customer properties and the control margin of the heat distribution center in the customer property.

The time delay for heat distribution from the power plant can be up to 8 hours to the extremes of the district heating network.

Unnecessary amounts of heat and pressure may therefore be pumped into the district heating network for safety reasons, so that the use of heating energy and the amount of network losses are unnecessarily high.

On the other hand, in some situations, the heat and pressure supplied to the district heating network may be insufficient in relation to the actual heat demand, resulting in a deficient level of service in the customer properties.

Korean patent publication KR 20160059849 A discloses an information system for a district heating network, which is adapted to provide real-time information on the status of heat supply to customer heat to a heat producer.

However, the problem in the information system according to the prior art = is the flood of information to the heat producer.

When a huge amount of information is provided to a heat producer = about customer properties, it is difficult for the heat producer to interpret this flood of information = 30 and make decisions about the total space of the heat supply based on it. in addition, the content N of the property-specific information may vary if the property-specific measuring devices differ.

The object of the invention is to provide a district heating network RTD (real time demand) information system and network losses while ensuring a good level of service in customer properties.

The features of the present invention appear from the appended claim 1. It is also an object of the invention to provide a method for collecting and utilizing RTD information which can significantly reduce the energy consumption and network losses of heat production while ensuring a good level of service in customer properties.

The characteristic features of the method of the present invention

The information system for the district heating network according to the invention comprises at least one power plant, a heat distribution network including branched heat transfer pipelines and pumping stations, and a number of customer properties with separate heat distribution centers and its own measuring device, which includes means for collecting measurement data = from the customer system.

The information system is adapted to collect information from the customer properties on the state of heat supply = enabling the heat producer to adjust the parameters of the district heating network> heat production to meet the requirements of the customer properties according to a preselected criterion.

In at least several customer properties, the metering equipment includes a control unit for calculating a key-performance-index (KPI) value from the relative capacity data from a plurality of components according to a preselected calculation criterion, for recording the KPI and transmitting the KPI to the heat generator. The system is adapted to provide real-time information on the status of heat supply to customer properties to the heat producer in reduced information bundles, including at least the KPI value of the customer property and the identification data of the customer property. The system comprises display means for displaying the KPI value to the heat generator.

In this way, the heat producer receives information on the status of heat supply to customer properties and the control space of heat distribution centers in an easy-to-interpret form, when an individual customer provides only one numerical value (KPI) to the customer's satisfaction with heat supply quality. Different properties may even calculate their value differently, but give a uniform value to the heat producer, who can control his own heat supply according to it. In this case, the heat producer does not have to interpret the information provided by each customer property separately, as the customer properties may have different heat supply devices and measuring devices or a different number of heating circuits. At the same time, the amount of data traffic is also reduced when it is not necessary to send measurement data from dozens of sensors from an individual customer property. All in all, this enables the optimization of flow temperatures in the network, the optimization of pressure, the reduction of heat and transmission losses in the district heating network and a good level of service in customer properties.

x a o In addition to the KPI value, the information bundle contains at least customer = 30 property identification information. The identification information includes at least N location information. In this case, the heat producer knows where the KPI value N has come from and can combine the information bundles regionally, whereby the heat producer receives information about the regional heat supply status of the branching pipes.

The heat producer can form regional information entities from the information trees of the customer properties, which comprise the relative capacity information of the regional customer properties. In this case, the pressure and temperature of the heat transfer tubes can be adjusted regionally.

The KPI value can be displayed to the heat generator on the display means as a numerical value or with various symbols.

In one embodiment of the invention, the system comprises at least a heating network return water temperature sensor and a district heating return water temperature sensor, for the difference of which the system is adapted to give a score according to a preselected criterion, which rating is one component for generating a KPI value. This tells you how well the target transfers energy. If the inlet temperature decreases, this indicator will decrease.

In one embodiment of the invention, the system includes at least a heating valve opening sensor and a hot water valve opening sensor, for the readings of which the system is adapted to give scores according to a preselected criterion, which scores are components for generating a KPI-O value. In this way, information is obtained = how much control space there is still in the heat distribution center. If there is a large amount of control space left in several properties, = heat output can be reduced. On the other hand, if the valves are almost completely open at several sites, it may be necessary to increase the heat output. If the valves are slightly open, then N heat transfer works well. If, on the other hand, it is almost completely open, then N temperature and pressure can no longer be lowered.

In one embodiment of the invention, the system comprises at least a heating network flow temperature sensor and a district heating inlet water temperature sensor, for which the system is adapted to assign a rating according to a preselected criterion, which rating is one component for generating a KPI value. This provides information on the relative capacity of the customer property. If the temperature difference falls short, it is no longer possible to reduce the efficiency of heat production.

In one embodiment of the invention, the system comprises at least a heating network flow temperature sensor and a hot water flow temperature sensor, the difference between the readings of which the system is adapted to give a score according to a preselected criterion, which is one component for generating a KPI. In this way, a sufficient amount of heat is ensured to heat the object. In one embodiment of the invention, the system includes at least a district heating inlet pipe pressure sensor and a district heating return pipe pressure sensor, the reading of which the system is adapted to give a score according to a preselected criterion, which score is one component for generating a KPI O. This provides information on the relative capacity of the customer's property. e Preferably, the system comprises the necessary software and = storage means with which the system is adapted to form> regional information entities and to store = 30 optimal levels of heat supply temperature at different outdoor temperatures and adapted to pre-adjust district heating network heat production parameters in advance. time delay. In this way, the learning information system made possible by RTD information

The system seeks the optimal level of heat supply temperature and pressure at different outdoor temperature points, which means that network losses can be significantly reduced while ensuring a good level of service in customer properties.

The optimal level refers to a temperature that is high enough to meet the heat demand of customer properties, but low enough not to supply unnecessary energy to the district heating network.

The invention also relates to a method in connection with a district heating network comprising at least one power plant, a heat distribution network including branched heat transfer pipelines and pumping stations, and its own measurement equipment, including means for collecting measurement data from the customer system.

In the method according to the invention, information is collected from customer properties on the state of heat supply, enabling the heat producer to adjust the heat production parameters of the district heating network on the basis of user-specific information to meet the requirements of customer properties according to a preselected criterion.

At least in several customer properties, the relative capacity is measured, O 25 from which the key factor value, or KPI (key-performance- = index) value, which is a numerical value formed from several components according to a pre-selected calculation criterion, is recorded, and the KPI value is transmitted. value to the heat producer.

Real-time information on the status of heat supply to customer properties = 30 is provided to the heat producer as reduced information n, comprising at least the KPI value of the customer property and the identification data of the N customer properties.

The KPI value is given in

to the producer.

This enables the optimization of flow temperatures in the network, the optimization of pressure, the reduction of heat and transmission losses in the district heating network and a good level of service in customer properties. Preferably, the information trees are formed into regional information entities and the parameters of the branched heat transfer pipelines of the district heating network are adjusted to change the regional pressure or temperature of the district heating network according to a preselected criterion. In this case, heat production can be reduced and / or the pressure in the piping can be reduced, which reduces network losses if the RTD information shows that the level of service that meets the criterion is achieved in customer properties with significantly less heat and / or pressure. Correspondingly, heat production can be increased and / or the pressure in the pipeline can be increased if the RTD information shows that the level of service in customer properties is insufficient. In this context, a set of information refers to regional entities formed from KPI values, which can be used to form an overall picture of the heat supply status of customer properties connected to different heat transmission pipelines in the district heating network.

Preferably, the selected components are graded according to a preselected criterion, and the scores are averaged to form a KPI, except that at least one component is given the worst possible score, with the KPI being the worst possible score. In this way, the information about the heat supply status of the customer property e can be packaged in an easy-to-read format at the end of the customer property. 2 o 30 The components used to calculate the KPI value may be 2 to N 20, preferably 4 to 10, and the components N are formed by reading a temperature sensor or a valve opening degree sensor or a pressure sensor of a customer's heat distribution center or a combination thereof. In this way, a KPI value J can be formed that sufficiently describes the state of the heat supply of the customer property from the quantities describing the state of the heat supply.

Preferably, the data of the customer property is compared with the data of the branch of the nearby heat transfer pipeline and the deviation is calculated according to a preselected criterion. In this way, information is obtained on the status of the heat supply and possible equipment faults.

Preferably, the time distribution of the heat distribution is taken into account so that the heat generator slows down the reading of the information bundle according to the time delay, if necessary. In large cities, the time delay for heat distribution can be up to 8 hours from the main power plant to the ends of the network. RTD information enables an intelligent and learning system that can apply the optimal level of heat supply temperature at different outdoor temperature points, taking into account the time delay, whereby network losses can be significantly reduced while ensuring a good level of service in customer properties.

Preferably, the optimal level for the heat supply temperature at different outdoor temperature points is stored and the heat production parameters of the district heating network are adjusted in advance at different outdoor temperature points according to the weather forecast, taking into account the heat and heating time delay. In this way, the learning = information system enabled by RTD information retrieves the optimal level of heat supply temperature and pressure at different outdoor temperature points, = where network losses can be significantly reduced while> ensuring a good level of service in customer properties. At the optimal level, 30 means a temperature that is high enough to meet the heat demand of customer properties, but low enough not to supply unnecessary energy to the district heating network.

Preferably, as the demand for heat supply in the district heating network increases above a predetermined limit value, the water flow in the heating network is reduced to improve the cooling of the district heating network in at least some of the customer properties. In this case, the ever-decreasing flow of district heating water to the customer's property will transfer energy. This adds more capacity to the network for other customers during consumption peaks, allowing district heat production to be maintained at a more even fuel efficiency.

The invention will now be described in detail with reference to the accompanying drawings, in which Figure 1 shows a process diagram of the operation of a heat distribution center according to the invention, and Figure 2 shows a schematic diagram of the operation of a district heating network according to the invention.

Figure 1 shows a heat distribution center 10 according to the invention as a process diagram. The supply line 36 of the district heating distribution pipeline 34 transports hot district heating water from the power plant 102 for use by the customer property 110. The hot district heating water passes through the heating valve 41 and the hot water valve 42 of the control system 20 and circulates in the heat exchangers = 50, heating each selected application. According to Figure 1, the application e can be the water of the heating piping 52 = water of the building or the water of the domestic water piping 54. The district heating water cooled from the heat exchangers 50> is returned to the power plant 102 via the return line 38 of the distribution pipeline 34 = 30.

e heating network flow temperature sensor 12, e district heating return water temperature sensor 13, e heating network return water temperature sensor 14, e hot water flow temperature sensor 15, e heating valve opening degree sensor 21, e hot water valve opening temperature sensor 22, e hot water valve opening degree sensor 22, e return pipe pressure sensor 32.

The metering equipment is connected to a control unit 70, which calculates one KPI value for the object based on the measured values, and transfers it to the cloud service power plant 102 for use in optimizing energy production. The following example discusses the generation of a single KPI value in a client property 110.

The KPI value in this case is defined on a three-point scale so that e level 1 is poor, e level 2 is satisfactory, and e level 3 is good. o In this embodiment, the components of the RTD information in the heat distribution center are: = 25 1. The difference between the readings 2 of the district heating supply water temperature sensor 11 and the heating network flow temperature sensor 12. level 1: 0 - 5% € S. level 2: 5 —- 10 ° C S 30 e level 3: above 10 ° C

2. Difference between level 1 of the district heating return water temperature sensor 13 and the heating network return water temperature sensor 14: more than 5 ° C 5. level 2: 3-5 ° C. level 3: 0-3 ° C

3. The difference between the readings 10 of the district heating supply water temperature sensor 11 and the domestic hot water flow temperature sensor 15. level 1: 0 - 5 ”C. level 2: 5 -— 10 ° C e level 3: above 10 ° C

4. Reading of the heating valve opening sensor 21. level 1: 90 - 100% 15. level 2:50 - 90%. level 3: 0 - 50%

5. The level e of the hot water valve opening sensor 22 is 1: 75 - 100%. level 2: 30 - 75% 20. level 3: 0 - 30% In other embodiments of the invention, for example, the difference between the readings 31 of the district heating inlet pipe N and the district heating return pipe pressure sensor 32-25 or other measuring variables 2 suitable for the property can also be used as components of the RTD information. Thus, different customer properties 110 can generate RTD information in different ways, but in a single customer QR property 110 one KPI value is always calculated, whereby the heat producer receives information about the relative capacity of the customer properties 110 in a uniform format.

If any of the above components of the RTD information is 1, then it is the determining factor. The total level is then 1. Otherwise, the KPI value is taken as the average of the components. This is calculated at the local level and transferred to the cloud service, where it is read for use by the network user and combined with a map-based network data model that can be used to control the city's heat production and pumping. At the main level, the residence time of the district heating is taken into account by slowing down the data if necessary. Levels can be changed by network.

The goal is that no object in the city is at level 1 but all are at level 2. In this case, the individual objects can be at level 3. In this case, the heat supply temperature is at the optimal level. There may be more than 3 levels of KPIs, for example 10, for a more accurate control effect. Level 1 items are reviewed individually and eliminated by adjustments or component changes. By doing so, the temperature level and pumping throughout the city can be reduced. Example 1: o 1. The reading of the district heating inlet water temperature sensor 11 is 0 to 75 ° C and the reading of the heating network flow temperature = sensor 12 is 67 ° C, where the difference e is 8 ° C. In this case, the level is 2. = 2. The reading of the district heating return water temperature sensor 13 is 60 ° C and the reading of the heating network return water temperature sensor 14 is 56 ° C, whereby the difference between these is 4 ° C. In this case, the level is 2. N 3. The reading of the district heating inlet water temperature sensor 11 is 70 ° C and the reading of the domestic hot water temperature sensor

The reading is 58 ° C, with a difference of 12 ° C. This is level 3.

4. The reading of the heating valve opening sensor 21 is 70%. This is level 2.

5. The reading of the hot water valve opening sensor 22 is 50%. In this case, we are at level 2. The average of the levels defined above is 2.2. This can be rounded to a KPI of 2, which is transferred to the cloud service and delivered to power plant 102. The goal is for all sites in the district heating network 100 to be at level 2. Example 2:

1. The reading of the district heating supply water temperature sensor 11 is 80 ° C and the reading of the heating network flow temperature sensor 12 is 72 ° C, whereby the difference between these is 8 ° C. This is level 2.

2. The reading of the district heating return water temperature sensor 13 is 60 ° C and the reading of the heating network return water temperature sensor 14 is 56 ° C, whereby the difference between these is 4 ° C. This is level 2.

3. The reading of the district heating inlet water temperature sensor 11 is o 70 ° C and the reading of the hot water flow temperature sensor O 25 15 is 58 ° C, where the difference is 12 ° C. = This is level 3. e 4. The reading of the heating valve opening sensor 21 is = 70% $. In this case, the level is 2.> 5. The reading of the hot water valve opening sensor 22 = 30 is 80%. In this case, we are at level 1. Now the 5th component of the RTD information is at level 1, which is the determining factor. The KPI value of the object is recorded in the cloud service as 1.

Such items are reviewed individually and eliminated by adjustments or component replacements.

Example 3:

1. The reading of the district heating supply water temperature sensor 11 is 80 ° C and the reading of the heating network flow temperature sensor 12 is 68 ° C, whereby the difference between these is 12 ° C. This is level 3.

2. The reading of the district heating return water temperature sensor 13 is 45 ° C and the reading of the heating network return water temperature sensor 14 is 41 ° C, whereby the difference between these is 4 ° C. This is level 2.

3. The reading of the district heating supply water temperature sensor 11 is 70 ° C and the reading of the hot water flow temperature sensor 15 is 58 ° C, whereby the difference between these is 12 ° C. This is level 3.

4. The reading of the heating valve opening sensor 21 is 40%. This is level 3.

5. The reading of the hot water valve opening sensor 22 is 20%. In this case, we are at level 3. The average of the levels defined above is 2.8. This is rounded to a KPI of 3, which is transferred to the cloud service and delivered to power plant 102. Individual sites can be = at level 3, but if there are many sites at level 3, the heat / pressure of the district heating network 100 2 can be reduced, thus saving energy. Figure 2 shows in principle a district heating network 100 comprising at least one power plant 102, a number of branched heat transfer tubes 104, pumping stations 106 and a number of customer properties 110 with their own heat distribution centers 10 which determine their own KPI values. In heat transfer tubes

104 also has a plurality of temperature sensors 121 and pressure sensors 122. Power plant 102 reads the KPI values of the heat distribution centers 10 from the cloud service into its own analytics tool, thus obtaining good data from its network on how the objects are performing under any circumstances. The customer property 110 provides relative capacity information to the power plant 102 as an information bundle that includes, in addition to the KPI value, at least identification information that includes information about the location of the customer property 110. The power plant 102 may form regional information entities 200 from the customer property information trees that comprise the relative capacity information of the regional customer properties 110. In this case, the pressure and temperature of the heat transfer tubes 104 can be adjusted regionally. A map-based network data model similar to Figure 2 can be used to control the city's heat production and pumping. The goal is for all customer properties 110 to be at level 2. Individual customer properties 110 may be at level 3, but if there are many objects at level 3, it is an indication that the temperature and / or pressure of the heat transfer pipe 104 in the district heating network 100 can be lowered and thus save energy. If a large number of customer properties 110 are at O level 1, this is an indication that the heat supply is insufficient, necessitating an increase in the temperature and / or pressure e of the heat transfer piping 104. Individual Level 1 = customer properties 110 are reviewed individually and repaired with> site-specific adjustments and / or component replacements. Doing this = 30 will reduce the temperature level and pumping N throughout the city.

N The RTD information system described above can be used to implement the demand-side flexibility system described below.

but this flexibility system can also be implemented without an RTD information system.

The goal of the demand flexibility system is steady fuel efficiency in district heating production. "The aim is to be able to produce heat with the most economical fuels and methods for as long and evenly as possible.

The outdoor temperature can fluctuate significantly even during the day, as can the energy needs of customer properties.

The goal is that the district heating network can be used to balance this consumption.

Roughly, the flow temperature rises slightly hotter than would be required at that moment and sometimes drops slightly below the setpoint.

The heat distribution centers communicate backwards with RTD information, which is enough for them.

If the stock in the district heating network shows signs of dissatisfaction, demand elasticity can typically be introduced for a few hours.

This gives time to increase production capacity and drive it to destinations.

Or if there is a prospect of air condensation or declining demand, no further action is needed, saving money.

Demand flexibility or power limitation can be done from the customer's point of view, keeping the power taken from the network as constant as possible.

In practice, during the hot water peak, the O 25 heating power is reduced.

That is, the heating = flow rate or temperature is allowed to decrease and through this e the heating consumption is transferred to a different point in time. = In terms of power, the transition does take place, but it almost does not always bring real flexibility to the system, because in a site with a 2-drive = 30 hot water converter, a large part of the hot water N power comes from the district heating return water returning from the N heating converter.

In other words, in the sense of power, the transition takes place, but in practice at the expense of cooling.

Another starting point for demand elasticity is the need for a power plant. That is, the power plant gives a signal when they would like flexibility. Now that the flexibility is done by limiting the flow temperature, the power decreases, but it does not add capacity to the network in the same proportion. This is because when the flow is limited, the radiator valves start to open, the pressure-controlled pumps increase their speed. The flow in the system increases and the cooling begins to weaken. On the primary side of district heating, the flow is reduced proportionally less than the power. In other words, the capacity of the district heating inlet pipe is lost more than the capacity is limited from the property's point of view. As the problem approaches, the following steps are taken.

1. The need for elasticity of demand can first be verified by means of RID information.

2. Once the potential of the network has been used, demand elasticity measures will be launched.

3. The elasticity of demand shall be implemented in such a way that the capacity-limiting measures of the buildings are at least fully exploited in the network. Limiting the flow temperature is not the right method —- especially in areas with pressure-controlled pumps that increase the flow in connection with the power limit. In these locations, this type of o power constraint provides only an apparent benefit. S 25 4. The solution is to add a function to existing intelligent heat distribution centers, such as FögsuGST® from HögforsGST, which increases the delivery capacity of the district heating network by up to 50% more than what the properties> cut. The real estate involved in the flexibility is considerably less needed than with the other N methods and their effect is considerably greater for the N whole. In the method, during the power limitation, the water flow in the radiator network is reduced, which results in an improvement in the cooling of the network and the transfer of energy to the customer's property by the ever-decreasing flow of district heating water. The use of the property's capacity is limited, but the flow of district heating water drops considerably more. This adds more capacity to the network for other customers. The method also does not burden the property system with thermal expansion, and there is no risk of pipelines breaking. Together with the RTD information, significant flexibility potential is obtained for the entire network.

The overall solution presented above can be further enhanced by installing a system with a DHAC module in a few critical network sites, which will further increase the capacity and cooling of the district heating network. These systems work best if the property has a lot of heat exchangers that work efficiently. Preferably, the heat exchangers are long exchangers that have the ability to operate at lower flows with good cooling. The right basic adjustments of the radiator networks also help the whole to work better. O Before the next power limit, the local heating system can charge the heat as follows. The pump speed is reduced = and the flow temperature is raised at the same time. When the power limit e comes, there is warmer water than normal in the system. a 2 o 30 This can be applied especially in connection with the accumulator and with primary heat sources other than district heating.

OF

Claims (15)

PATENT REQUIREMENTS An information system for a district heating network (100), comprising at least one power plant (102), a heat distribution network containing branching heat transfer pipe systems (104) and pumping stations (106), and at the end of the branching pipes a plurality of customer properties (110) with its own heat distribution centers (10) comprising heat exchangers (50) and a control system (20) for controlling the district heating flow according to a set consumption and a separate measuring device, which comprises means for collecting measurement data from the customer system, which information system is arranged to collect information from customer properties (110) about the state of the heat supply enabling the heat producer to regulate the parameters of the district heating network (100) heat production on the basis of the user-specific information to meet the customer properties' (110) requirements in accordance with a pre-selected criterion , characterized in that N in at least several customer properties (110) comprises measuring devices no one control unit (70) for calculating an S key factor value or KPI (key-performance index) - S value formed from relative capacity information of E several sub-factors in accordance with a preselected 2 calculation criteria for registering the CPI value o 30 and for conveying the CPI value to the heat producer, the system is arranged to provide real-time information on the condition of the customer properties (110) heat delivery to the heat producer in the form of simplified information bundles comprising at least the said customer property's (110) CPI value and the customer property's (110) identification information, and the esystem comprises display means for presenting said CPI value to the heat producer. Information system according to claim 1, characterized in that the system comprises at least one temperature sensor (14) for the heating water return water and a temperature sensor (13) for the district heating return water, for the difference of which readings the system is arranged to give a rating in accordance with a preselected criterion, which grade is a sub-factor for the formation of the CPI value. Information system according to claim 1 or 2, characterized in that the system comprises at least one opening degree sensor (21) for the heating valve and an opening degree sensor (22) for the domestic water valve, the readings of which the system is arranged to give a certificate in accordance with a pre-selected criteria, which grades are sub-factors for the formation of the CPI value. Information system according to one of Claims 1 to 3, characterized in that the system comprises at least one temperature sensor (12) for the heating network outflow and a temperature sensor (11) for the district heating inflow, for the difference E of the readings. the system is arranged to give a rating in accordance with a preselected criterion, which rating is a sub-factor for forming the CPI value. S Information system according to one of Claims 1 to 4, characterized in that the system comprises at least one temperature sensor (12) for the outflow of the heating network and a temperature sensor (15) for the outflow of the domestic water, for the difference of which readings the system is arranged to provide a grade in accordance with a pre-selected criterion, which grade is a sub-factor for the formation of the CPI value. Information system according to one of Claims 1 to 5, characterized in that the system comprises at least one pressure sensor (31) for the district heating inlet pipe and a pressure sensor (32) for the district heating return pipe, for the difference of which readings the system is arranged to give a grade in in accordance with a pre-selected criterion, which grade is a sub-factor for the formation of the CPI value. Information system according to one of Claims 1 to 6, characterized in that the system comprises the necessary software and storage means, with which the system is arranged to form regional information units (200) and to store an optimal level for the heat supply temperature at different outdoor temperature points. arranged to regulate the parameters for the district heating network's heat production in advance at different outdoor temperature points in accordance with the weather forecast, taking into account the time distribution of the heat distribution. S 25 s 8. A method in connection with a district heating network (100), which s district heating network (100) comprises E e at least one power plant (102), o a heat distribution network containing branching o heat transfer pipe system (104) and pumping stations O (106), and at the end of the branch pipes customer properties (110) with their own heat distribution centers (10) comprising heat exchangers (50) and a control system (20) for controlling the district heating flow according to a set consumption and a separate measuring device, which comprises means for collecting measurement data from the customer system, in which method information is collected from customer properties (110) about the state of the heat supply enabling the heat producer to regulate the parameters of the district heating network (100) heat production on the basis of the user-specific information in order to meet the requirements of the customer properties (110) in accordance with a pre-selected criterion, characterized in that e in at least several customer properties (110) the relative capacity, from which a key factor value or KPI (key-performance-index) value, which is a numerical value formed by several sub-factors in accordance with a pre-selected calculation criterion, the CPI value is registered and the CPI value is communicated to the heat producer, e information is provided in real time about the state of the heat supply of the properties (110) to the heat producer in the form of simplified information bundles comprising at least said KPI value of said customer property (110) and the identification information of N customer property (110), and N 25 e said KPI value is presented to the heat producer. & J Method according to claim 8, characterized in that regional information units (200) are formed from said information bundles and the parameters of the district heating network (100) and branching heat transfer pipe system (104) are regulated to change the regional pressure or temperature of the district heating network (100). in accordance with a pre-selected criterion. Method according to claim 8 or 9, characterized in that grades are given for selected sub-factors in accordance with a pre-selected criterion and from the grades a mean value is calculated which forms said CPI value excluding a situation where at least one sub-factor is given the worst possible grade, whereby the worst possible grade is formed as said CPI value. Method according to any one of claims 8 - 10, characterized in that there are 2 - 20, preferably 4 - 10 said sub-factors used to calculate said KPI value, and said sub-factors are formed from the readings of the customer property (110 ) heat distribution centers (10) any temperature sensor or valve opening degree sensor or pressure sensor or a combination of these. Method according to one of Claims 8 to 11, characterized in that the data of the customer property (110) are compared with the branch data of a nearby heat transfer pipe system (104) and the deviation is calculated in accordance with a preselected criterion. - 25 N Method according to one of Claims 8 to 12, characterized in that the time delay of the heat distribution is taken into account so that the heat producer, if necessary, makes the reading of said information bundle slower in accordance with the time delay. 2 o Method according to one of Claims 8 to 13, characterized in that the optimum level for the heat supply temperature at different outdoor temperature points is stored and the parameters for the district heating network's heat production are regulated in advance at different outdoor temperature points in accordance with the weather forecast. of the time distribution of the heat distribution. Method according to one of Claims 8 to 14, characterized in that when the heat supply demand of the district heating network (100) exceeds a predetermined limit value in at least a part of the customer properties (110), the water flow of the heating network is restricted to improve the district heating network (100). cooling. N O N © <Q < N I jami a (> <r © O N O N